analysis of milk and egg allergens in wine using uplc-ms - waters corporation food safety

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©2015 Waters Corporation 1 Analysis of Milk and Egg Allergens in Wine Using UPLC-MS Work performed in collaboration with:

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©2015 Waters Corporation 1

Analysis of Milk and Egg Allergens

in Wine Using UPLC-MS

Work performed in collaboration with:

©2015 Waters Corporation 2

Presentation Overview

Background

– Allergenic proteins in wine

– MS technology for allergen analysis

Establishing a Routine Workflow on

Tandem Quad MS

– QTof to Tandem quad MS

– Software to Tandem quad MS

Conclusions

©2015 Waters Corporation 3

Milk and Egg Proteins for Wine Clarification

Clarification is an important step in wine making

– Remove phenolic compounds (e.g. tannins)

Fining agents include egg whites (albumin) and

milk (casein)

– Forms insoluble complex that settles at the bottom

– Wine is filtered to remove these finings

– Minimal quantities are used to achieve the desired

result without stripping too much flavour

Finings should be removed when the wine is

clarified.

In some countries it is a legal requirement to

state any potential allergens on the label

©2015 Waters Corporation 7

Analysis of Allergens Popular Technologies Adopted

ELISA

PCR

MS In

creasin

g C

urren

t U

sag

e

In

creasin

g I

nstr

um

en

t C

om

ple

xit

y &

Pric

e

©2015 Waters Corporation 8

What information can MS detection provide?

Analyse peptide markers of the protein causing the

allergic reaction

Targeted and specific m/z analysis

Quantifiable technique

Capability to modify / optimise routine methods for

challenging matrices (without additional cost)

Potential to use a multi-allergen approach

©2015 Waters Corporation 9

Strategy 1

Instrument-based strategy to identify egg

and milk peptide markers using

Xevo G2 QTof MS

©2015 Waters Corporation 10

Bottom-up Proteomic Experiment

1. Enzyme digestion

2. UPLC separation

Precursor ions

MSE product ions

3. MS analysis

4. Data interpretation

©2015 Waters Corporation 11

Food Proteomic Workflow

SAMPLE PREPARATION (1) Tryptic digest (2) ADH addition

DATA ACQUISITION Acquire data-independent MSE Data

SOFTWARE PROCESSING PLGS & IdentityE and Proteomic database (e.g. UniProt)

ANALYTICAL SYSTEMS (1) ACQUITY UPLC ® (2) XevoTM G2 QTof

©2015 Waters Corporation 13

Food Proteomics Workflow Software processing

High energy product ion data gives increased confidence in peptide sequence identification

Markers are from a SINGLE protein

Unique marker peptides sequences listed here

©2015 Waters Corporation 14

Xevo G2 QTof advantages for determining suitable peptide markers…

NN

PFYFPSR

DLAFPG

SG

EQ

VEK

VLLEEN

AG

GEQ

EER

ISM

PVN

TPG

QFED

FFPASSR

©2015 Waters Corporation 15

VERIFYE

Transferring research data to routine analysis

Exact mass data is translated into MRMs with VERIFYE

©2015 Waters Corporation 16

VERIFYE …Proteotypic Peptide Review …MRM Method Generation

©2015 Waters Corporation 17

Strategy 2

Software-based strategy to identify peptide

markers

©2015 Waters Corporation 18

Skyline Experimental Design

Peptide settings

Transition settings

MRM generation

©2015 Waters Corporation 19

Skyline versus VERIFYE

Advantages

– Good solution for customers who have invested in tandem quad MS

for allergen analysis

Disadvantages

– Skyline can provide 100s potential MRM transitions

– Need to work through the list to determine

• Specificity for the matrix

• Sensitivity of the transition

– VERIFYE uses the QTof data and so the list is from instrumental

data

©2015 Waters Corporation 20

Milk and egg allergen in milk: Sample prep development

Samples:

– Red and white wine, fortified before/after extraction

Tested extraction/concentration protocols:

1. Ultrafiltration (cut-off 3kDa and 10 kDa)

2. precipitation with acetone

3. precipitation with acetone/TCA

4. precipitation with KDS

5. precipitation with ethanol

Protein pellet suspended in a solution of 120mM Tris 7M urea 2M thiourea

Best sample prep results:

– Precipitation with cold acetone or ethanol

©2015 Waters Corporation 23

ACQUITY UPLC parameters

(ACQUITY UPLC parameters have not yet been fully optimised)

LC system ACQUITY UPLC I-Class

Column BEH130 C18 UPLC column 2.1 x 150mm

Flow rate 0.5ml/min

Column temp 40°C

Solvent A Water + 0,1% formic acid

Solvent B ACN 0,1% formic acid

Time(min) A B

Initial 85 15

1.00 85 15

11.00 30 70

12.00 30 70

12.50 0 100

14.00 0 100

15.50 85 15

17.00 85 15

©2015 Waters Corporation 24

Milk allergens: Targeted peptides and MRMs

Peptide Precursor

(m/z) Product (m/z)

YLGYLEQLLR (casein S1) 423.2 529.3

634.4 658.4

634.4 771.5

634.4 934.5

VPQLEIVPNSAEER (casein S1) 527.6 802.4

790.9 779.5

790.9 802.4

790.9 1014.5

FFVAPFPEVFGK (casein S1) 692.9 465.2

692.9 676.4

692.9 920.5

692.9 991.5

ALNEINQFYQK (casein S2) 456.6 827.4

684.3 713.4

684.3 827.4

684.3 940.5

FALPQYLK (casein S2) 490.2 332.2

490.2 551.3

490.2 648.4

490.2 761.5

©2015 Waters Corporation 25

Egg allergens: Targeted peptides and MRMs

Peptide Precursor (m/z)

Product (m/z)

DILNQITKPNDVYSFSLASR (ovalbumin) 761.0 767.4

761.0 930.5

761.0 1355.7

1141.1 1355.7

GGLEPINFQTAADQAR (ovalbumin) 563.3 732.4

844.4 860.4

844.4 1007.5

844.4 1121.5

844.4 1331.7

ELINSWVESQTNGIIR (ovalbumin) 620.3 673.4

620.3 888.5

930.0 1017.5

930.0 1116.6

EVVGSAEAGVDAASVSEEFR (ovalbumin) 670.3 853.4

670.3 924.4

1005.0 1110.5

1005.0 1266.6

©2015 Waters Corporation 26

Peptide Identification & Confirmation Using ACQUITY UPLC & Xevo TQ-S

1. Retention time

2. Standard MRM transitions

©2015 Waters Corporation 27

Peptide Identification & Confirmation Using ACQUITY UPLC & Xevo TQ-S

1. Retention time

2. Standard MRM transitions

3. Standard MRM transitions & full scan data

4. Product ion scanning confirmation

(PICs)

©2015 Waters Corporation 28

Method Development with Skyline Use of RADAR for Food Matrices

- Parallel MRM with full scan data acquisition

}

©2015 Waters Corporation 29

Method Development with Skyline Use of RADAR for Food Matrices

Once the most selective, and then the most sensitive MRMs have been selected for a subset of

food matrices, RADAR can be used to support routine analysis

Casein

S1-

YLG

Casein

S1-

FFV

Ovalb

um

in-

EVV O

valb

um

in-

GG

L

Ovalb

um

in-

DIL

O

valb

um

in-

ELI

Casein

S2-

FAL

Casein

S1 -

VPQ

Casein

S2-

ALN

4

3

2 1

6

5

Full scan

MRMs

©2015 Waters Corporation 30

Peptide Protein Charge state: m/z

GPFPIIV β-CN +1: 742.4490

FFVAPFPEVFGK α-S1-CN +2: 692.8695

HQGLPQEVLNENLLR α-S1-CN +2: 880.4770

YLGYLEQLLR α-S1-CN +2: 634.3568

Comparing RADAR data with Journal Citations

L. Monaci, I. Losito, F. Palmisano, M. Godula & A. Visconti (2011): Food Additives & Contaminants: Part A: Chemistry, Analysis, Control, Exposure & Risk Assessment, 28:10, 1304-1314

XIC of m/z 742.4

RT – 5.33 or 6.13

©2015 Waters Corporation 31

Peptide Identification & Confirmation Additional confirmation using PICs

Food processing can affect peptide response observed and there

may be other similar proteins present in complex food products

– PEPTIDE SPECIFICITY is essential

PIC scan for peptide

DLAFPGSGEQVEK

y and b ion fragments(*)

*

* *

*

*

* *

*

*

©2015 Waters Corporation 32

Peptide Identification & Confirmation Additional confirmation using PICs

PIC scan for peptide marker

FFVAPFPEVFGK

found in Casein S1

Matrix: White wine

©2015 Waters Corporation 33

Peptide Identification & Confirmation Additional confirmation using PICs

PIC scan for peptide marker

FFVAPFPEVFGK

found in Casein S1

Matrix: Red wine

©2015 Waters Corporation 34

Compound name: YLGYLEQLLR (casein S1)

Correlation coefficient: r = 0.995512, r^2 = 0.991045

Calibration curve: 59440.7 * x + -3078.23

Response type: External Std, Area

Curve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

1000000

2000000

3000000

4000000

5000001

Compound name: ALNEINQFYQK (casein S2)

Correlation coefficient: r = 0.995324, r^2 = 0.990670

Calibration curve: 4296.6 * x + -289.732

Response type: External Std, Area

Curve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

100000

200000

300000

Compound name: FALPQYLK (casein S2)

Correlation coefficient: r = 0.996969, r^2 = 0.993948

Calibration curve: 62929.5 * x + 567.125

Response type: External Std, Area

Curve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

1000000

2000000

3000000

4000000

5000001

Compound name: GGLEPINFQTAADQAR (ovalbumin)

Correlation coefficient: r = 0.992720, r^2 = 0.985493

Calibration curve: 26267.2 * x + -5862.54

Response type: External Std, Area

Curve type: Linear, Origin: Exclude, Weighting: 1/x, Axis trans: None

Conc0 10 20 30 40 50 60 70 80 90 100

Re

sp

on

se

0

500000

1000000

1500000

2000000

2500000

Matrix-match calibration curves

©2015 Waters Corporation 35

Software Tools for Long-Term Routine Allergens Analysis

©2015 Waters Corporation 36

Conclusions

Existing allergens methods employ ELISA & PCR-based techniques

Recent years interest in tandem quad MS

– Increased selectivity

– Potential for multi-allergen analysis

– Capability to modify LC-MS methods for challenging matrices / proteins

affected during the food processing

Routine methods need MRMs to be selective and sensitive to

identify and confirm the presence / absence allergenic protein(s).

Method development stage can be time-consuming & useful to

have additional tools to support process

– RADAR – parallel acquisition of full scan and MRM data

– PICS – additional peptide confirmation

– TrendPlot – long term monitoring: QC standards, samples…

©2015 Waters Corporation 37

Acknowledgements

CER Group

o Nathalie Gillard

o Olivier Spee

o Philippe Delahaut

Waters Corporation

o Lee Gethings

o Kelly McMahon